Underdetermined Blind Separation using Multi-Subspace Representation in Time-Frequency Domain

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

Blind source separation (BSS) is a technique to recognize the multiple talkers from the multiple observations received by some sensors without any prior knowledge information. The problem is that the mixing is always complex, i.e., nonlinear, underdetermined mixture, such as the case where sources are mixed with some direction angles, or where the number of sensors is less than that of sources. In this paper, we propose a multi-subspace representation based BSS approach that allows the mixing process to be nonlinear and underdetermined. The approach relies on a multi-layer representation and sparse representation in time-frequency (TF) domain. By parameterizing such subspaces, we can map the observed signals in the feature space with the coefficient matrix from the parameter space. We then exploit the linear mixture in the feature space that corresponds to the nonlinear mixture in the input space. Once such subspaces are built, the coefficient matrix can be constructed by solving an l1-regularization on the coding coefficient vector. Relying on the TF representation, the target matrix can be constructed in a sparse mixture TF vectors with a fewer computational cost. The experiments are run on the observations that are generated from nonlinear functions, and that are collected with some direction angles in a virtual room environment. The proposed approach exhibits a higher separation accuracy than that of the conventional algorithms.

元の言語English
ホスト出版物のタイトル2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
出版者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781538680889
DOI
出版物ステータスPublished - 2019 5 1
イベント2019 IEEE International Conference on Communications, ICC 2019 - Shanghai, China
継続期間: 2019 5 202019 5 24

出版物シリーズ

名前IEEE International Conference on Communications
2019-May
ISSN(印刷物)1550-3607

Conference

Conference2019 IEEE International Conference on Communications, ICC 2019
China
Shanghai
期間19/5/2019/5/24

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

フィンガープリント Underdetermined Blind Separation using Multi-Subspace Representation in Time-Frequency Domain' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

    Wang, L., & Ohtsuki, T. (2019). Underdetermined Blind Separation using Multi-Subspace Representation in Time-Frequency Domain. : 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings [8761133] (IEEE International Conference on Communications; 巻数 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC.2019.8761133